A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

Catalysts that efficiently transfer hydrogen for storage in organic hydrogen carriers are key for more sustainable generation and use of hydrogen. New research identifies activity descriptors that can accelerate novel catalyst development.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

1-propanol converts from a monomer into a trimer at aluminum sites within zeolite pores.

The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.

Studying single crystal reactions provides molecular-level insight into catalytic processes.

Highly precise and controllable single-atom catalysts are affected by reaction conditions, which can alter the bonding around the atoms and the activity.

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

Water affects the intermediates present on the surface of a metal oxide catalyst during ketonization.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.

A new system can convert common plastics into valuable fuel molecules.

Within zeolite pores, rates of alcohol dehydration increase with ionic strength until reaching a maximum and then decreasing.

In a water-containing system, the open circuit potential stabilizes positively charged species and lowers the energy barrier of the reaction.

A new approach broadens the reach of quantum computers to previously challenging systems.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

A new deep learning approach allows researchers to rapidly analyze three-dimensional representations of multi-component catalysts.

Using electrocatalysis offers a different path for reactions involving polar groups.

Where molybdenum dopants sit within catalytic material affects catalysis at a mechanistic level.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.